Detection of Non-XR/MD Detectable Foreign Objects in Meat

ABSTRACT

Disclosed is an inspection system having a background positioned adjacent an inspection zone; and an image capturing device configured to receive background electromagnetic radiation (EMR) from the background and from the inspection zone, the inspection zone being configured and arranged to receive material for transport into the inspection zone; wherein the background has a background property defined by a background emission, a background absorbance, and a background reflectance, the background property being matched in EMR to a material EMR of material to be transported into the inspection zone, the material having a material property defined by a material emission, a material absorbance, and a material reflectance; and wherein the image capturing device is configured to detect a foreign object within material when transported into the inspection zone by deducting the background EMR from the material EMR.

FIELD

Embodiments can relate to an inspection system having a backgroundpositioned adjacent an inspection zone, wherein an image capturingdevice receives electromagnetic radiation from the background and fromthe inspection zone to identify foreign objects traveling through theinspection zone.

BACKGROUND INFORMATION

Conventional inspection systems generally rely on x-ray (XR) orMahalanobis Distance (MD) techniques and are able to detect a wide rangeof contaminants and other quality related non-conformances. Yet, thereare some foreign object contaminants that cannot be detected by XR or MDtechniques, resulting in a non-Mt/MD detectable event. Non-XR/MDdetectable events are common for inspection systems used in meatprocessing systems (i.e., where the material being inspected is meat).Foreign objects leading to a non-XR/MD detectable event can includeitems such as cardboard, plastic materials from liners and conveyors,cutting knives and hooks, personal protective equipment such asearplugs, gloves, and hairnets, pocket items including pens, pencils,and candy wrappers, etc. Such events represent a significant cost andburden to the entities engaged in meat processing.

In addition, conventional systems cannot detect a foreign objectcontaminant being conveyed through the system in the absence of the meatflow (i.e., when no meat is being conveyed but the conveyor is runningand is transporting a foreign object that had been inadvertentlyentrained in the system).

Known means to remedy these deficiencies are the use of human inspectorsthat visually inspect the meat before or after it is transported throughthe XR and/or MD detector, but prior to the meat entering the grinder.Such techniques are labor intensive and are limited in effectiveness, ashuman inspectors are constrained to visual inspection and can onlyseeing the top layer of the meat. Yet, many foreign objects are hiddenwithin the meat or lie under the meat at the meat/conveyor interface. Inaddition, eye/vision fatigue experienced by human inspectors sets inafter a period of time, which further reduces the effectiveness of thehuman inspector to identify foreign objects.

Known inspection systems can be appreciated from DE 202006010023, EP3242124, US 20150336135, US 20160263624, and WO 2017048783. Knownsystems can be limited in that they cannot effectively and efficientlydetect non-XR/MD detectable events. Known systems are also limited intheir ability to detect foreign objects being conveyed through theprocessing system in the absence of meat flow.

SUMMARY

Embodiments can relate to an inspection system having a backgroundpositioned adjacent an inspection zone, an image capturing deviceconfigured to receive background electromagnetic radiation (EMR) fromthe background and from the inspection zone, the inspection zone beingconfigured and arranged to receive material for transport into theinspection zone. The background has a background property defined by abackground emission, a background absorbance, and a backgroundreflectance, the background property being matched in EMR to a materialEMR of material to be transported into the inspection zone, the materialhaving a material property defined by a material emission, a materialabsorbance, and a material reflectance. The image capturing device isconfigured to detect a foreign object within material when transportedinto the inspection zone by deducting the background EMR from thematerial EMR.

Embodiments can relate to a material processing system having a conveyorsystem having a conveyor belt configured to carry material, the conveyorbelt including an outfeed conveyor belt being positioned so that thematerial will fall through an inspection zone and land on the outfeedconveyor belt. The material processing system can include an inspectionsystem having: a background positioned adjacent the inspection zone; andan image capturing device configured to receive EMR from the backgroundand from the inspection zone, the inspection zone being configured andarranged to receive material for transport into the inspection zone. Thebackground has a background property defined by a background emission, abackground absorbance, and a background reflectance, the backgroundproperty being matched in EMR to a material EMR of a material to betransported into the inspection zone, the material having a materialproperty defined by a material emission, a material absorbance, and amaterial reflectance. The image capturing device is configured to detecta foreign object within material when transported into the inspectionzone by deducting the background EMR from the material EMR.

Embodiments can relate to a method for inspection involving positioninga background adjacent an inspection zone, the background having abackground property defined by a background emission, a backgroundabsorbance, and a background reflectance. The method can involvedirecting material of a material flow into the inspection zone, thematerial having a material property defined by a material emission, amaterial absorbance, and a material reflectance. The method can involvedetecting whether the material property differs from the backgroundproperty by at least deducting EMR of the background from EMR of thematerial.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features and advantages of the present disclosure will become moreapparent upon reading the following detailed description in conjunctionwith the accompanying drawings, wherein like elements are designated bylike numerals, and wherein:

FIG. 1 shows an exemplary inspection system;

FIG. 2 show an exemplary configuration of an embodiment of theinspection system;

FIG. 3 shows another exemplary configuration of an embodiment of theinspection system;

FIG. 4 shows an exemplary configuration of an embodiment of a computerdevice that can be used with an embodiment of the inspection system;

FIG. 5 shows an exemplary material processing system that can be usedwith an embodiment of the inspection system; and

FIG. 6 shows an exemplary separator unit that may be used with anembodiment of the material processing system.

DETAILED DESCRIPTION

Referring to FIGS. 1-3, embodiments can relate to an inspection system100 having a background 102 positioned adjacent an inspection zone 104,and an image capturing device 106 configured to receive backgroundelectromagnetic radiation (EMR) from the background and from theinspection zone 104, the inspection zone 104 being configured andarranged to receive material for transport into the inspection zone 104.

The inspection system 100 can be an apparatus designated for inspectingmaterial entering into and/or passing through an inspection zone 104 todetermine if the material is a foreign object and/or determine if thematerial has a foreign object entrained therein (e.g., a foreign objectmixed in it, on top of it, underneath it, etc.). For instance, theinspection system 100 may be part of a material processing system 500(e.g., a meat processing system). The material processing system 500 canhave a conveyance system that causes the material to pass through theinspection zone 104. The inspection zone 104 can be a designated area ofthe material processing system 500 used to inspect the material forquality assurance purposes. It is contemplated for the inspection zone104 to be an area of the conveyance system through which the materialfalls through in a free-fall. For example, the conveyance system caninclude a conveyor belt 502 having an infeed conveyor belt 502 a and anoutfeed conveyor belt 502 b, the infeed conveyor belt 502 a beingpositioned relative to the outfeed conveyor belt 502 b so that thematerial will fall from the infeed conveyor belt 502 a, travel throughan inspection zone 104, and land on the outfeed conveyor belt 502 b. Theportion of the conveyance system where the material falls from theinfeed conveyor belt 502 a to the outfeed conveyor belt 502 b can bereferred to as a waterfall region 504. Having the inspection zone 104configured as a designated area for inspection of material entering afree-fall can be beneficial in that the inspection system 100 can betterbe able to detect foreign objects that would otherwise lie underneaththe layer of meat while on the conveyor belt 502.

The inspection system 100 can be used to identify whether any materialpassing through the inspection zone 104 is a substance other than meat.Thus, the inspection system 100 can identify an object (whether it iswithin the meat, separate from the meat, passing through the inspectionzone 104 simultaneously with the meat, passing through the inspectionzone 104 in the absence of meat, etc.) passing through the inspectionzone 104 as a substance other than meat. For instance, the inspectionsystem 100 can determine if the meat flow passing through the inspectionzone 104 has been contaminated with a foreign object (e.g., a piece ofequipment from the material processing system 500 has worked loose andis being transported by the conveyance system along with the meat)and/or determine if a foreign object passes through the inspection zone104 even if no meat is being transported through the inspection zone 104(e.g., a worker has lost a glove and it is being transported by theconveyance system in the absence of meat being flowed through thesystem). The foreign object can be any substance not anticipated to bepart of the meat or meat mix, such as cardboard, plastic materials fromliners and conveyors, cutting knives and hooks, personal protectiveequipment such as earplugs, gloves, and hairnets to pocket itemsincluding pens, pencils, candy wrappers, etc.

The inspection system 100 can have a background 102 positioned adjacentthe inspection zone 104. The inspection zone 104 can be a volume ofspace designated for conducting inspection of material entering into theinspection zone 104. The background 102 can be an object (e.g., a sheet,a backboard, etc.) placed adjacent (e.g., in proximity to, abuttingagainst, etc.) this volume of space so that at least a portion of thebackground 102 is within a field of view (the angular extent of a givenscene) of the volume of space. As will be explained herein, being withinthe field of view will allow EMR from an illumination source 200 to bedirected to both the inspection zone 104 and the background 102, andallow EMR emitted from both material within the inspection zone 104 andthe background 102 to be received by the image capturing device 106.

The background 102 can be configured to have a background propertydefined by a background emission, a background absorbance, and abackground reflectance, the background property being matched in EMR toa material EMR of material to be transported into the inspection zone104, the material having a material property defined by a materialemission, a material absorbance, and a material reflectance. Forinstance, the background property can be configured to have opticalproperties that match those of the material (e.g., meat), but not thatof any anticipated foreign objects. It is possible for a foreign object(e.g., a non-anticipated foreign object) to have optical properties thatmatch those of the background property, but the chances of thiseventuality occurring is expected to be low. For instance, if thematerial is meat and the meat is being processed by a meat processingsystem, it can be determined with a high level of statistical certaintywhat the optical properties of the meat will be (because the compositionof the meat mix will be known due to the meat is being processed undercontrolled conditions) and what the optical properties of the foreignobjects will be due to the limited number of possible foreign objectsthat can exist under such controlled conditions. Thus, the materialproperty of meat can have a signature material emission, a signaturematerial absorbance, and a signature material reflectance, and thebackground can have a background emission, a background absorbance, anda background reflectance that matches, or at least substantially matchesthe meat's signature material emission, a signature material absorbance,and signature material reflectance so that the background property, whendetected by optical equipment, appears the same as the meat property. Inother words, the optical equipment may not detect a difference in EMRemitted therefrom when comparing the background property to the materialproperty. However, because the anticipated foreign object is expected tohave a foreign object property (e.g., a foreign object emission, aforeign object absorbance, and a foreign object reflectance) thatdiffers from those of the meat and the background, the optical equipmentwill detect a difference in EMR emitted therefrom when comparing thebackground property to the foreign object property.

While it is contemplated for the inspection system 100 to operate bydetecting and comparing optical properties, such as emission,absorbance, and reflectance, other optical properties (e.g., refraction,polarization, photoluminescence, transmittance, diffraction, dispersion,dichroism, scattering, birefringence, photosensitivity, etc.) can beused in addition to or in the alternative of emission, absorbance, andreflectance.

The image capturing device 106 can be configured to detect a foreignobject within material when transported into the inspection zone 104 bydeducting the background EMR from the material EMR. The image capturingdevice 106 can be positioned so that the inspection zone 104 and atleast a portion of the background 102 are within the field of view ofthe image capturing device 106. The image capturing device 106 can be anoptical apparatus configured to receive EMR and analyze the EMR based onthe wavelength, amplitude, phase, polarization, etc. For instance, theimage capturing device can include a lens, a charged coupled device(CCD), and circuitry (e.g., processor, filter circuits, etc.) to receiveEMR, process it, and generate an output that is the EMR comparison (thededuction of the background EMR from the material EMR). Use of the lensand the CCD for the image capturing device are exemplary, and it shouldbe understood that optical elements and sensors in addition to or in thealternative of the lens and the CCD can be used.

The circuitry of the image capturing device 106 can be configured tocompare the background property to the material property by comparingthe background EMR it receives from the background 102 to the materialEMR it receives from material entering into the inspection zone 104. Oneway to achieve this is to deduct the background EMR from the receivedEMR. For instance, the image capturing device 106 can receive EMR fromthe inspection zone 104 (whether there is material or foreign objectspassing through or not) and receive EMR from the background 102. Theimage capturing device 106 can perform signal processing operations(e.g. Fourier transform or other operation) to allow for mathematicalrepresentation and manipulation of the received EMR. The image capturingdevice 106 then deducts the background EMR from the received EMR (e.g.,subtracts values representative of amplitude, frequency, phase, etc. ofthe background EMR from values representative of amplitude, frequency,phase, etc. of the received EMR). When no material or foreign object ispassing through the inspection zone 104, the image capturing device willonly receive the background EMR as the received EMR, wherein deductingthe background EMR from the received EMR in this case will result inbackground EMR, which can be defined as a negative reading (meaning noforeign object detected). When only material that is meat is passingthrough the inspection zone 104, the image capturing device will receivethe background EMR and the material EMR as the received EMR, whereindeducting the background EMR from the received EMR in this case willresult in a null reading because the background EMR and the material EMRare matched, which again can be defined as a negative reading. When onlymaterial that is a foreign object is passing through the inspection zone104, the image capturing device will receive the background EMR and theforeign object EMR as the received EMR, wherein deducting the backgroundEMR from the received EMR in this case will result in an EMR differencebecause the background EMR and the foreign object EMR are not matched,which can be defined as a positive reading (meaning that a foreignobject has been detected). When material that is meat and a foreignobject is passing through the inspection zone 104, the image capturingdevice will receive the background EMR, the material EMR, and theforeign object EMR as the received EMR, wherein deducting the backgroundEMR from the received EMR in this case will again result in a positivereading because the background EMR and the foreign object EMR are notmatched.

As noted herein, the background property can be configured to match orsubstantially match that of the material property (e.g., the meat). Asthere will be some variance in the material property (due to thedifferent types of meat and meat mixes being processed), a thresholdrange can be set when performing the EMR comparison. For instance, ifthe EMR comparison results in a difference in EMR when the deduction ismade, but that difference is within a predetermined threshold range thenit still may be considered a negative reading.

As can be appreciated from the above analyses, making such a comparison(deducting the background EMR from the received EMR) facilitatesdetecting a foreign object passing into the inspection zone 104regardless of whether meat is also passing into the inspection zone 104.It should also be noted that the image capturing device 106 can make thecomparison by deducting the background EMR from the received EMR or bydeducting the received EMR from the background EMR.

In some embodiments, the inspection system 100 can include the materialpositioned in the inspection zone 104. In some embodiments, theinspection system 100 can include the foreign object within the materialpositioned in the inspection zone 104. As noted herein, some embodimentsof the inspection system 100 can be configured to inspect the materialthat is meat.

Some embodiments of the inspection system 100 can include a computerdevice 108 in operative communication with the image capturing device106, the computer device 108 having a display 110 for displaying animage or graphical representation of the material property and thebackground property. The computer device 108 can be a processor inoperative association with a memory. The memory can include computerprogram code stored thereon.

Any of the processors disclosed herein can be at least a one of ascalable processor, a parallelizable processor, etc. Any of theprocessors can be optimized for multi-thread processing capabilities. Insome embodiments, the processor can be a graphics processing unit (GPU).The processor can include any integrated circuit or other electronicdevice (or collection of devices) capable of performing an operation onat least one instruction, which can be any one or combination of aReduced Instruction Set Core (RISC) processor, a CISC microprocessor, aMicrocontroller Unit (MCU), a CISC-based Central Processing Unit (CPU),a Digital Signal Processor (DSP), etc. The hardware of such devices maybe integrated onto a single substrate (e.g., silicon “die”), ordistributed among two or more substrates. Various functional aspects ofthe processor may be implemented solely as software or firmwareassociated with the processor.

The memory can be optionally associated with the processor. Embodimentsof the memory can include a volatile memory store (such as RAM),non-volatile memory store (such as ROM, flash memory, etc.) or somecombination of the two. For instance, the memory can include, but is notlimited to, RAM, ROM, EEPROM, flash memory, CDROM, digital versatiledisk (DVD) or other optical storage, magnetic cassette, magnetic tape,magnetic disk storage or other magnetic storage device, or any othermedium which can be used to store the desired information and that canaccessed by the processor. The memory can be a non-transitorycomputer-readable medium. The term “computer-readable medium” (or“machine-readable medium”) as used herein is an extensible term thatrefers to any medium or any memory that participates in providinginstructions to the processor for execution, or any mechanism forstoring or transmitting information in a form readable by a machine(e.g., a computer). Such a medium may store computer-executableinstructions to be executed by a processing element, control logic,and/or data which are manipulated by a processing element and/or controllogic, the medium being able to take many forms, including but notlimited to, non-volatile medium, volatile medium, and transmissionmedia.

Transmission media can include coaxial cables, copper wire and fiberoptics, which can include the wires that include or form a bus.Transmission media can also take the form of acoustic or light waves,such as those generated during radio-wave and infrared datacommunications, or other form of propagated signals (e.g., carrierwaves, infrared signals, digital signals, etc.). Forms ofcomputer-readable media include, for example, a floppy disk, a flexibledisk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM,any other optical medium, punch-cards, paper-tape, any other physicalmedium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM,any other memory chip or cartridge, a carrier wave as describedhereinafter, or any other medium from which a computer can read.

Instructions for implementation of any of the methods disclosed hereincan be stored on the memory in the form of computer program code. Thecomputer program code can include program logic, control logic, or otheralgorithms that may or may not be based on artificial intelligence(e.g., machine learning techniques, artificial neural networktechniques, etc.). The memory and the computer program code can beconfigured to cause the processor associated therewith to implement anyof the methods disclosed herein.

The computer device 108 can have a display 110 configured to display animage or graphical representation of the background property, thematerial property, and/or the foreign object property. For instance, theimage capturing device 106 can generate an output signal that isrepresentative of the EMR comparison (e.g., the deduction of thebackground EMR from the received EMR) for a point within a grid, thegrid being a virtual geometric plane passing through a longitudinal axisof the inspection zone 104. The point on the grid can be a coordinatepoint (e.g., a Cartesian coordinates) of the grid so that a plurality ofoutput signals can represent an EMR comparison from a plurality ofpoints on the grid. The computer device 108 can receive these signalsand generate an image or graphical representation of the EMR comparisonat a point in time for the plurality of output signals. The inspectionsystem 100 can be configured to transmit the output signals from theimage capturing device 106 to the computer device 108 (and the computerdevice 108 can generate a display of the same) on a continuous basis,periodic basis, as dictated by a user of the inspection system 100, orby some other scheme. The computer device 108 can transmit the image orgraphical representation to the display 110. The display 110 can displaythe image or graphical representation by causing a pixel to generate apredetermined color for a negative reading and another predeterminedcolor for a positive reading. A user viewing the display 110 canascertain that a foreign object has passed into the inspection zone 104by viewing the different colors of the pixels on the display. In someembodiments, the computer device 108 can be equipped with a clock, andassign a timestamp to each output signal received by the image capturingdevice 106. The image or graphical representation can then be displayedon the display 110 along with the timestamp, allowing a user todetermine when a foreign object has passed into the inspection zone 104.

In some embodiments, the background property is selected as a functionof a material which includes a first material and a foreign objectmaterial, wherein the first material has a first material property andthe foreign object material has a second material property. The firstmaterial property equals the background property, and the secondmaterial property does not equal the background property. As notedherein, the background property can be configured to have opticalproperties that match those of the material (e.g., meat or the firstmaterial) but not that of any anticipated foreign objects. For instance,the first material property can have a first material signature materialemission, a first material signature material absorbance, and a firstmaterial signature material reflectance, and thus the background canhave a background emission, a background absorbance, and a backgroundreflectance that matches, or at least substantially matches the firstmaterial's signature material emission, signature material absorbance,and signature material reflectance so that the background property, whendetected by optical equipment, appears the same as the first material(or meat) property. The anticipated foreign object is expected to have asecond material property (e.g., a second material emission, a secondmaterial absorbance, and a second material reflectance) that differsfrom those of the first material and the background, and thus theoptical equipment will detect a difference when comparing the backgroundproperty to the second material property.

As noted herein, embodiments of the processors for the image capturingdevice 106 and/or the computer device 108 can have computer program codestored thereon that is based on artificial intelligence. The artificialintelligence can be configured to provide machine learning for theinspection system 100 so as to optimize detection. In an exemplaryembodiment, the artificial intelligence can be configured to useadversarial learning techniques during image processing for detectionoptimization.

Conventional image processing methods use a multivariate statisticaltechnique for detecting outliers (e.g., the Mahalanobis Distance (MD)),which utilize a single feature vector: color. This is calculated from a3-dimensional RGB (color) input space, where the distance in thetransformed space from each target pixel to the trained or “learned”distribution of “meat colors” determines whether that pixel is a “meat”or “not meat” color. In this technique, color is the sole feature vectorproviding discrimination between “meat” and “not meat”. In effect, MD isproviding anomaly detection, where the presence of a “not meat” colorregion in an image is an anomaly. These anomalies are then classified asforeign objects.

One of the problems with conventional MD methods is that certain classesof foreign objects may be very similar to “meat color”, or may betranslucent/transparent where they do not exhibit a color but appear tobe the same color as whatever object may be in their background.Further, how the foreign objects are presented in the meat matrix (wherethey are presented as a result of reflected and transmitted light fromprimary illumination sources and secondary reflection from theillumination source in the inspection zone) can confound colordiscrimination. This limits how well the system “learns” duringsupervised learning, but also limits discrimination performance atrun-time, which can increase false reject rate.

In addition, some foreign object classes that consist of man-made(manufactured) product, regardless of color, exhibit signature spatialfeatures discriminable from natural product like meat, like straightedges (or more generally, edge characteristics), precisely repeatableforms (example: texture in fabric), or fine/dispersed distributiondisjoint forms (example: fiber in cardboard), precise parallels,concentricities, regular geometric forms (example: tape, washers, coins,o-rings), etc., which can render anomaly detection via MD difficult. Forinstance, practically, it cannot be known a priori how (and to whatextent) the discriminant hyperplane in that space will be determined bythe feature vectors (and combinations thereof). Furthermore, it is notpractical to use a technique that requires an exhaustive training setdue to the universe of foreign object classes/specimens being boundless.Thus, there is a large set (actually open-ended set) of “spatial”feature vectors that the conventional algorithmic methods arenaïve/blind to. Combined with color feature vector(s), this set ofspatial feature vectors poses a very high dimension data space.

Embodiments of the adversarial learning technique, however, utilize aconvolutional neural network (CNN), which can be used as part ofGenerative Adversarial Network or “GAN”. CNNs and GANs are based on deeplearning techniques that center on effective methods in high dimensiondata spaces. More particularly, the GAN can be configured so that twonetworks compete “adversarially” with each other during training: onenetwork (“generator”) generates real negative images and fake negativeimages (negative meaning no foreign objects) from random noise; theother network (“discriminator”)—which has access to the trainingimages—attempts to discern (classify) which of the images from thegenerator are real and which are fake. These two networks can be placedinto a feedback loop with each other, in which the generator “learns” bybecoming more proficient at generating fake images that can fool thediscriminator, while the discriminator “learns” by becoming moreproficient at not being fooled (i.e., better at discerning thedifference between real and fake images). This technique for anomalydetection can provide a significant advance in any imaging-basedinspection application (optical, IR, x-ray, etc.).

Embodiments of the adversarial learning technique can provide thefollowing advantages

-   -   Training set. Typically, it is difficult and expensive to create        large populations of images with foreign object samples required        by conventional methods. Embodiments of the adversarial learning        technique, however, can use a large population of negative        images (i.e., no foreign objects), which are easily and        essentially cost-fee to acquire.    -   Unsupervised Learning. Conventional methods require “supervised        learning”, meaning the system is trained using samples that are        labeled (i.e., it is known a priori what class each sample        belongs to). Embodiments of the adversarial learning technique,        however, can utilize unsupervised learning, where it is left to        the algorithm to develop and discern these distinctions.    -   Generalization. A characteristic advantage neural network        algorithms in classification schemes is their ability to        “generalize”: They do not need to have exhaustive training to        address every possible input state. When presented with novel        input, they will tend to classify accurately, at least within        the dimensions of their feature vector space. In vision        applications, that translates into a substantially enhanced        ability to discern subtle and perhaps incomplete patterns in a        noisy image, without the tendency to fail catastrophically        (something that simple thresholding and pixel counting often        do).    -   Extensibility. Embodiments of the adversarial learning technique        can be extended to incorporate additional feature vectors from        other imaging modalities, including NIR and XR, for example.    -   Limitation of Mahalanobis Distance. MD can work well, but only        when the underlying data sets are normal and unimodal.        Embodiments of the adversarial learning technique are not        reliant on normal and unimodal data sets. In addition, MD is        less than effective with chroma discrimination within low        saturation colors, which tend to predominate in imaging for meat        processing.    -   Embodiments of the adversarial learning technique do not rely on        a human (qualified or not) to determine appropriate training or        discriminant functionality. Instead, the system can develop        these itself from adversarial training.

In some embodiments, the inspection system 100 can include anillumination source 200 configured to generate and direct EMR into theinspection zone 104 so that the EMR will interact with the background102 and will interact with the material when the material travels intothe inspection zone 104. The illumination source 200 can be anincandescent lamp, halogen lamp, a light emitting diode, a laser, an IRlight generator, a UV light generator, an x-ray generator, etc. It iscontemplated for the illumination source 200 to be a stroboscopic lampso as to provide the requisite EMR intensity for effective and efficientoperation of the inspection system 100. For instance, the intensity ofthe EMR required to analyze meat being conveyed in a material processingsystem 500 would be high, thus a stroboscopic lamp (e.g., in continuousmode for example) would be able to generate the requisite intensity inan efficient manner.

In some embodiments, illumination source 200 can be configured togenerate EMR having a wavelength in the visible spectrum. While theillumination source 200 can be configured to generate EMR at anywavelength in the EMR spectrum, it is contemplated for the illuminationsource to generate EMR in the visible spectrum (e.g., wavelengths withinthe range from 400 nm to 700 nm). It is further contemplated for theillumination source to generate white light (light comprising all, orsubstantially all, of the wavelengths in the visible spectrum, each withequal, or substantially equal, intensity).

The image capturing device 106 can be an optical camera (e.g., RGBcamera, HLS camera, etc.). With embodiments of the inspection system 100configured to analyze EMR of the visible spectrum, the image capturingdevice 106 can be an optical camera. However, if in addition or in thealternative, the EMR analysis includes an analysis of EMR outside of thevisible spectrum, the image capturing device 106 can be or include othercomponents for such analysis (e.g., an antenna, a telescope, aspectroscope, an IR detector or camera, a NIR detector or camera, a UVdetector or camera, X-ray detector, etc.)

In an exemplary embodiment, the material can include a first materialand a foreign object material, wherein the first material has a firstmaterial property and the foreign material has a second materialproperty. The first material property can cause the EMR interactedtherewith to be within the red color spectrum and the backgroundproperty can cause the EMR interacted therewith to be within the redcolor spectrum. As noted herein, the material can be meat, such as bulkflow of trim meat (e.g., beef, pork, lamb, turkey, chicken, etc.). Suchmeat (uncooked and unprocessed) generally has a red color (e.g., EMRemitted therefrom has wavelengths generally within the range from 625 nmto 675 nm). Thus, with embodiments where the first material is meat, thebackground 102 can be configured to have a background property such thatthe EMR emitted therefrom is a red color so as to match with the EMRemitted from the first material or the meat.

In some embodiments, the inspection zone 104 can be segmented by alongitudinal plane into a first inspection zone side 104 a and a secondinspection zone side 104 b. For instance, the inspection zone 104 can bebi-sected in the vertical direction by a longitudinal plane, forming afirst inspection zone side 104 a and a second inspection zone side 104b. In some embodiments, the background 102 can include a firstbackground 102 a located in the first inspection zone side 104 a and asecond background 102 b located in the second inspection zone side 104b. Any one or combination of the first background 102 a and the secondbackground 102 b can be arranged to be parallel or at any other anglewith respect to the longitudinal plane.

The material can travel into the inspection zone 104 between the firstbackground 102 a and the second background 102 b. The illuminationsource 200 can be configured to direct the EMR into the inspection zone104 so that the EMR will interact with the first background 102 a, thesecond background 102 b, and the material when the material travels intothe inspection zone 104. For instance, the illumination source 200 canbe positioned so that the EMR emitted therefrom is incident upon theinspection zone 104 (and any material or foreign object passing into theinspection zone 104), the first background 102 a, and the secondbackground 102 b. Some embodiments can include a plurality ofillumination sources 200. For instance, a first illumination source 200can be configured to emit EMR to be incident upon the inspection zone104 (and any material or foreign object passing into the inspection zone104) and the first background 102 a. A second illumination source 200can be configured to emit EMR to be incident upon the inspection zone104 (and any material or foreign object passing into the inspection zone104) and the second background 102 b.

In some embodiments, the image capturing device 106 can include a firstimage capturing device 106 and a second image capturing device 106. Thefirst image capturing device 106 can be configured to detect whether thematerial property differs from the background property of the firstbackground 102 a. The second image capturing device 106 can beconfigured to detect whether the material property differs from thebackground property of the second background 102 b. For instance, thefirst image capturing device 106 can be configured to perform the EMRcomparison with background EMR from the first background 102 a, and thesecond image capturing device 106 can be configured to perform the EMRcomparison with background EMR from the second background 102 b.

Referring to FIGS. 4-5, embodiments can relate to a material processingsystem 500 including a conveyance system having a conveyor belt 502configured to carry material. The conveyor belt 502 can include anoutfeed conveyor belt 502 b being positioned so that the material willfall through an inspection zone 104 and land on the outfeed conveyorbelt 502 b. In some embodiments, the conveyor belt 502 can include aninfeed conveyor belt 502 a and an outfeed conveyor belt 502 b. Theinfeed conveyor belt 502 a can be positioned relative to the outfeedconveyor belt 502 b so that the material will fall from the infeedconveyor belt 502 a, travel through an inspection zone 104, and land onthe outfeed conveyor belt 502 b. The portion of the conveyance systemwhere the material falls from the infeed conveyor belt 502 a to theoutfeed conveyor belt 502 b can be referred to as a waterfall region504. It will be appreciated that the conveyance system can be configuredto transport material via a continuous flow process or via a discrete orbatch flow process.

The material processing system 500 can include an inspection system 100having a background 102 positioned adjacent the inspection zone 104, andan image capturing device 106 configured to receive EMR from thebackground 102 and from the inspection zone 104, the inspection zone 104being configured and arranged to receive material for transport into theinspection zone 104. For instance, an embodiment of the inspectionsystem 100 can be incorporated with or used with a material processingsystem 500.

Embodiments of the inspection system 100 used in or with the materialprocessing system 500 can be configured so that the background 102 has abackground property defined by a background emission, a backgroundabsorbance, and a background reflectance, the background property beingmatched in EMR to a material EMR of a material to be transported intothe inspection zone 104, the material having a material property definedby a material emission, a material absorbance, and a materialreflectance.

The image capturing device 106 can be configured to detect a foreignobject within material when transported into the inspection zone 104 bydeducting the background EMR from the material EMR.

In some embodiments, the material is meat and the foreign object is acontaminant.

In some embodiments, the material processing system 500 can include acomputer device 108 in operative communication with the image capturingdevice 106, the computer device 108 having a display 110 for displayingan image or graphical representation of the background property and thematerial property.

The computer device 108 can include a control module 400 to control theoperation of the conveyor belt 502. The control module 400 can be aprocessor or other circuitry and mechanics configured to controloperational aspects of the conveyance system, such asactivation/deactivation of the conveyor belt 502 (e.g., the infeedconveyor belt 502 a, the outfeed conveyor belt 502 b, or any combinationof both), speed of the conveyor belt 502, directional flow of thematerial in the conveyance system, etc. As noted herein, it iscontemplated for the inspection system 100 to be used to inspect meat.In this regard, the inspection system 100 can be used to identify anyforeign object that has entered the conveyance system before the meat isfurther processed by the material processing system 500. Thus, theinspection system 100 can be configured so that the inspection zone 104is positioned at a point in the conveyance system before the meat isprocessed (e.g. grinded). Upon detecting that a foreign object hasentered into the inspection zone 104, the computer device 108 cantransmit a signal to the control module 400 to cause the control module400 to stop the conveyor belt 502, divert the material that is suspectedto have the foreign object to a rejection bin, divert the material thatis suspected to have the foreign object to a further inspection process,etc. The computer device 108 can transmit the signal automatically. Inaddition or in the alternative, a user of the computer device 108 cancause the transmission of the signal after the computer device 108indicated that the foreign object has been detected (e.g., the computerdevice 108 displayed the image or graphical representation of theforeign object on the display 110). For instance, the computer device108 can also generate a user interface via the display 110 that allows auser to issue commands and control aspects of the inspection system 100and/or material processing system 500.

For instance, in an exemplary embodiment, meat (after passing theinspection zone 104—which can be the waterfall region 504) will land onthe outfeed conveyor belt 502 b for further conveyance and processing.One of the following actions can occur if a “Not Meat” condition isidentified (or a foreign object is identified): a) Meat will land on theoutfeed conveyor belt 502 b and the computer device 108 sends a rejectsignal to cause the outfeed conveyor belt 502 b and/or the infeedconveyor belt 502 a to stop, wherein a human operator will sort throughthe meat to find the foreign object. Once the foreign object has beenremoved, the human operator can restart the conveyance system via thecomputer device 108 and/or the control module 400, allowing the meat toproceed to the next stage of the process, or the human operator canremove the meat (along with the suspected foreign object) and re-insertit in to the material flow path for inspection by a the same ordifferent inspection technique (e.g., MD, NIR, XR, human inspection,etc.). b) Meat will land on an outfeed conveyor belt 502 b equipped withan automated reject mechanism, wherein the foreign object detectionsignal will cause the control module 400 to actuate the automaticrejection mechanism so as to divert the material (and the suspectedforeign object) to a rejection bind for disposal or for additionalsorting by a human operator. If sent for additional sorting, once theforeign object has been removed, the previously rejected material can bere-inserted to the material flow path (e.g., in a portion of the paththat is before the inspection zone 104 so as to allow for the materialto be inspected again) or into a material flow path for inspection byanother method. c) Meat (the portion suspected to have the foreignobject) will be diverted to a reverse-retracting outfeed conveyor belt502 b, while meat (not suspected of having the foreign object) will bedirected to an outfeed conveyor belt 502 b for further processing (e.g.,grinding). The meat that lands on the reverse-retracting outfeedconveyor belt 502 b will be direct to a rejection bind for disposal orfor additional sorting by a human operator. If sent for additionalsorting, once the foreign object has been removed, the previouslyrejected material can be re-inserted to the material flow path (e.g., ina portion of the path that is before the inspection zone 104 so as toallow for the material to be inspected again) or into a material flowpath for inspection by another method.

In some embodiments, the user interface, along with the display of theimage or graphical representation of the material and foreign object,can assist with identification and removal of the foreign object fromthe rejected material. For instance, the display 110 can display imagesof the suspected foreign object that caused the rejection to occur so asto allow the operator to see exactly what they are searching for in thematerial in order to speed up the process and deliver positiveconfirmation of the foreign object being sought.

In some embodiments, the outfeed conveyor belt 502 b can be configuredas a rejection path to direct the material to a rejection bin as adefault unless the inspection system 100 detects a negative reading.Upon detecting a negative reading, the outfeed conveyor belt 502 b canre-direct the meat to an accepting bin or acceptance path. In otherwords, the material processing system 500 can be configured toautomatically direct the meat towards a rejection bin as a fail-safeuntil it is confirmed that a batch of meat contains no foreign objects(e.g., no positive readings were detected), at which time the outfeedconveyor belt 502 b re-directs that batch of meat to an acceptance binor acceptance path.

Referring to FIG. 6, in some embodiments, the material processing system500 a separator unit 600 configured to separate and remove the foreignobject from the conveyor belt 502. A separator until 600 can be amechanical switch (e.g., a flap sorting switch) in operativecommunication with the control module 400 that, when activated, causesthe material to follow an alternative route. For instance, the outfeedconveyor belt 502 b can comprise segments of conveyor belts 502, atleast one of which is pivotally attached so as to allow it to swing likea flap. When all the segments are in alignment (e.g., the flappingsegment is not actuated), the material flows over the segments in acontiguous manner. When the flapping segment is actuated, it rotates(e.g. downward) to allow material to be directed downward and fallthrough to another outfeed conveyor belt 502 b that is locatedunderneath the segmented outfeed conveyor belt 502 b. When theinspection system 100 detects a foreign object, the computer device 108can track the position of the suspected foreign object based on thetimestamp, the grid coordinates, and the speed of the conveyance system.Either at a user's discretion (e.g., via the user interface) orautomatically by the computer device 108, the control module 400 can beused to control the separator unit 600 and cause the portion of thematerial suspected to have the foreign object to be removed from thematerial stream to allow for removal of the foreign object. Once theforeign object has been removed, the formally rejected material can bere-inserted it in to a material flow path for inspection by a differentinspection technique (e.g., MD, NIR, XR, human inspection, etc.) and/orthe inventive inspection technique.

Embodiments can relate to a method for inspection. The method caninvolve positioning a background 102 adjacent an inspection zone, thebackground having a background property defined by a backgroundemission, a background absorbance, and a background reflectance.

The method can involve directing material of a material flow into theinspection zone 104, the material having a material property defined bya material emission, a material absorbance, and a material reflectance.

The method can involve detecting whether the material property differsfrom the background property by at least deducting EMR of the backgroundfrom EMR of the material.

In some embodiments, the method can involve directing EMR into theinspection zone 104 so that the EMR will interact with the background102 and will interact with the material when the material travels intothe inspection zone 104.

In some embodiments, the method can involve segmenting the inspectionzone 104 by a longitudinal plane into a first inspection zone side 104 aand a second inspection zone side 104 b. The method can further involvepositioning a first background 102 a in the first inspection zone side104 a and a second background 102 b in the second inspection zone side104 b.

In some embodiments, the method can involve directing EMR into theinspection zone 104 so that EMR will interact with the first background102 a, the second background 102 b, and the material when the materialtravels into the inspection zone.

In some embodiments, the method can involve displaying an image orgraphical representation of the material property and the backgroundproperty.

In some embodiments, the method can involve separating and removingmaterial from the material flow when the material property differs fromthe background property.

It will be understood that modifications to the embodiments disclosedherein can be made to meet a particular set of design criteria. Forinstance, any other component or process step can be any suitable numberor type of each to meet a particular objective. Therefore, while certainexemplary embodiments of the system and method of using and making thesame have been discussed and illustrated, it is to be distinctlyunderstood that the invention is not limited thereto but can beotherwise variously embodied and practiced within the scope of thefollowing claims.

It will be appreciated that some components, features, and/orconfigurations can be described in connection with only one particularembodiment, but these same components, features, and/or configurationscan be applied or used with many other embodiments and should beconsidered applicable to the other embodiments, unless stated otherwiseor unless such a component, feature, and/or configuration is technicallyimpossible to use with the other embodiment. Thus, the components,features, and/or configurations of the various embodiments can becombined together in any manner and such combinations are expresslycontemplated and disclosed by this statement.

It will be appreciated by those skilled in the art that the presentinvention can be embodied in other specific forms without departing fromthe spirit or essential characteristics thereof. The presently disclosedembodiments are therefore considered in all respects to be illustrativeand not restricted. The scope of the invention is indicated by theappended claims rather than the foregoing description and all changesthat come within the meaning and range and equivalence thereof areintended to be embraced therein. Additionally, the disclosure of a rangeof values is a disclosure of every numerical value within that range,including the end points.

What is claimed is:
 1. An inspection system, comprising: a backgroundpositioned adjacent an inspection zone; and an image capturing deviceconfigured to receive background electromagnetic radiation (EMR) fromthe background and from the inspection zone, the inspection zone beingconfigured and arranged to receive material for transport into theinspection zone; wherein the background has a background propertydefined by a background emission, a background absorbance, and abackground reflectance, the background property being matched in EMR toa material EMR of material to be transported into the inspection zone,the material having a material property defined by a material emission,a material absorbance, and a material reflectance; and wherein the imagecapturing device is configured to detect a foreign object withinmaterial when transported into the inspection zone by deducting thebackground EMR from the material EMR.
 2. The inspection system recitedin claim 1, in combination with the material positioned in theinspection zone.
 3. The inspection system recited in claim 2, incombination with the foreign object within the material positioned inthe inspection zone.
 4. The inspection system recited in claim 1,wherein: the material is meat.
 5. The inspection system recited in claim1, comprising: a computer device in operative communication with theimage capturing device, the computer device having a display fordisplaying an image or graphical representation of the material propertyand the background property.
 6. The inspection system recited in claim1, wherein: the background property is selected as a function of amaterial which includes a first material and a foreign object material,wherein the first material has a first material property and the foreignobject material has a second material property; the first materialproperty equals the background property; and the second materialproperty does not equal the background property.
 7. The inspectionsystem recited in claim 1, comprising: an illumination source configuredto generate and direct EMR into the inspection zone so that the EMR willinteract with the background and will interact with the material whenthe material travels into the inspection zone.
 8. The inspection systemrecited in claim 1, comprising: an illumination source configured togenerate and direct EMR into the inspection zone so that the EMR willinteract with the background and will interact with the material whenthe material travels into the inspection zone; wherein: the illuminationsource is configured to generate EMR having a wavelength in the visiblespectrum; the image capturing device is an optical camera; the materialincludes a first material and a foreign object material; the firstmaterial has a first material property and the foreign material has asecond material property; and the first material property causes the EMRinteracted therewith to be within the red color spectrum and thebackground property causes the EMR interacted therewith to be within thered color spectrum.
 9. The inspection system recited in claim 1,comprising: an illumination source configured to generate EMR; theinspection zone is segmented by a longitudinal plane into a firstinspection zone side and a second inspection zone side; the backgroundincludes a first background located in the first inspection zone sideand a second background located in the second inspection zone side; thematerial will travel into the inspection zone between the firstbackground and the second background; and the illumination source isconfigured to direct the EMR into the inspection zone so that the EMRwill interact with the first background, the second background, and thematerial when the material travels into the inspection zone.
 10. Theinspection system recited in claim 9, wherein: the image capturingdevice includes a first image capturing device and a second imagecapturing device; the first image capturing device is configured todetect whether the material property differs from the backgroundproperty of the first background; and the second image capturing deviceis configured to detect whether the material property differs from thebackground property of the second background.
 11. A material processingsystem, comprising: a conveyor system having a conveyor belt configuredto carry material, the conveyor belt including an outfeed conveyor beltbeing positioned so that the material will fall through an inspectionzone and land on the outfeed conveyor belt; and an inspection systemhaving: a background positioned adjacent the inspection zone; and animage capturing device configured to receive electromagnetic radiation(EMR) from the background and from the inspection zone, the inspectionzone being configured and arranged to receive material for transportinto the inspection zone; wherein: the background has a backgroundproperty defined by a background emission, a background absorbance, anda background reflectance, the background property being matched in EMRto a material EMR of a material to be transported into the inspectionzone, the material having a material property defined by a materialemission, a material absorbance, and a material reflectance; the imagecapturing device is configured to detect a foreign object withinmaterial when transported into the inspection zone by deducting thebackground EMR from the material EMR.
 12. The material processingrecited in claim 11, wherein: the material is meat and the foreignobject is a contaminant.
 13. The material processing recited in claim11, comprising: a computer device in operative communication with theimage capturing device, the computer device having a display fordisplaying an image or graphical representation of the backgroundproperty and the material property; wherein the computer device includesa control module to control the operation of the conveyor belt.
 14. Thematerial processing recited in claim 11, comprising: a separator unitconfigured to separate and remove the foreign object from the conveyorbelt.
 15. A method for inspection, the method comprising: positioning abackground adjacent an inspection zone, the background having abackground property defined by a background emission, a backgroundabsorbance, and a background reflectance; directing material of amaterial flow into the inspection zone, the material having a materialproperty defined by a material emission, a material absorbance, and amaterial reflectance; and detecting whether the material propertydiffers from the background property by at least deductingelectromagnetic radiation (EMR) of the background from EMR of thematerial.
 16. The method recited in claim 15, comprising: directing EMRinto the inspection zone so that the EMR will interact with thebackground and will interact with the material when the material travelsinto the inspection zone.
 17. The method recited in claim 15,comprising: segmenting the inspection zone by a longitudinal plane intoa first inspection zone side and a second inspection zone side; andpositioning a first background in the first inspection zone side and asecond background in the second inspection zone side.
 18. The methodrecited in claim 17, comprising: directing EMR into the inspection zoneso that EMR will interact with the first background, the secondbackground, and the material when the material travels into theinspection zone.
 19. The method recited in claim 15, comprising:displaying an image or graphical representation of the material propertyand the background property.
 20. The method recited in claim 15,comprising: separating and removing material from the material flow whenthe material property differs from the background property.